MIMO systems promise significant capacity gains. When perfect CSI is available at the transmitter, precoding can further improve the performance. However, the performance is limited by the eigen layer having the least SNR. Coordinate Interleaved Spatial Multiplexing has been proposed recently, in which the performance of weaker eigen layers is improved at the expense of a degraded performance in the stronger layers. It has been showed that interleaving improves the overall performance of the system when the eigen layers have different diversities. Previous work on CISM assumes equal power to all the eigen layers. In this paper, we propose a power allocation approach to improve the performance of the scheme. We derive expressions for power allocation to the interleaved streams based on an optimality criterion, which tries to minimize the error probability. Simulations confirm our analytical results and show the improvement in performance. © 2010 IEEE.

R. David Koilpillai

Department of Electrical Engineering

Analytical results

Capacity gain

Degraded performance

Error probabilities

OPTIMALITY CRITERIA

Power allocations

Precoding

SPATIAL MULTIPLEXING

Decoding

MIMO systems

Probability

signal processing

Multiplexing

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IIT Madras

A novel power allocation approach for coordinate interleaved spatial multiplexing

2010 International Conference on Signal Processing and Communications, SPCOM 2010

Performance of spatial multiplexing multiple-input multiple-output (MIMO) wireless systems can be improved with channel state information (CSI) at both ends of the link. This paper proposes a new linear diagonal MIMO transceiver, referred to as co-ordinate interleaved spatial multiplexing (CISM). With CSI at transmitter and receiver, CISM diagonalizes the MIMO channel and interleaves the co-ordinates of the input symbols (from rotated QAM constellations) transmitted over different eigenmodes. The analytical and simulation results show that with co-ordinate interleaving across two eigenmodes, the diversity gain of the data stream transmitted over the weaker eigenmode becomes equal to that of the data transmitted on the stronger eigenmode, resulting in a significant improvement in the overall diversity. The diversity-multiplexing tradeoff (DMT) is analyzed for CISM and is shown that it achieves higher diversity gain at all positive multiplexing gains compared to existing diagonal transceivers. Over rank n MIMO channels, with input symbols from rotated n-dimensional constellations, the DMT of CISM is a straight line connecting the endpoints (0,NtNr) and (min{Nt,Nr}, 0), where Nt, and Nr} are the number of transmit and receive antennas, respectively. © 2006 IEEE.

Fulltext

IEEE Transactions on Wireless Communications

Co-ordinate interleaved spatial multiplexing with channel state information

Vertical layering with successive interference cancellation (SIC) at the receiver (e.g. V-BLAST) is a popular spatial multiplexing scheme that achieves high data rates over multi-antenna wireless channels. However, SIC suffers from low diversity gains and recently, with limited feedback, a diversity optimal SIC receiver has been proposed based on greedy QR decomposition (GQR-SIC). But the low diversity gain of the first decoded layer degrades the overall diversity gain. In this paper, we present a new diagonally layered spatial multiplexing scheme that employs GQR-SIC receiver but achieves significantly higher diversity gains. In the proposed scheme, the diversity gain of a weak layer is improved through interleaving the co-ordinates of the symbols transmitted over the weak layer and a strong layer. In this work, we focus on spatial multiplexing with only two layers and analyze the diversity multiplexing tradeoff to show that the proposed scheme achieves maximum diversity gain. When compared with other diagonally layered schemes, the proposed scheme has low decoding complexity. © 2008 IEEE.

GLOBECOM - IEEE Global Telecommunications Conference

A new diagonally layered spatial multiplexing scheme with partial channel knowledge

IEEE Transactions on Signal Processing

Uniform channel decomposition for MIMO communications

Joint transceiver design for MIMO communications using geometric mean decomposition

Proceedings of the IEEE

An Overview of MIMO Communications—A Key to Gigabit Wireless

Journal	2010 International Conference on Signal Processing and Communications, SPCOM 2010
Open Access	No